Preprocessing of Mouse AD Pre-Frontal Cortex DIA Data - C2
Metadata
Experiment
CrossTab: Sex
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 73
| Genotype (5=FAD, 0=WT)
Sex (11=Female, 22=Male) | 0 | 5 | na | Row Total |
-------------------------|-----------|-----------|-----------|-----------|
11 | 9 | 20 | 0 | 29 |
| 1.100 | 0.498 | 5.562 | |
| 0.310 | 0.690 | 0.000 | 0.397 |
| 0.562 | 0.465 | 0.000 | |
| 0.123 | 0.274 | 0.000 | |
-------------------------|-----------|-----------|-----------|-----------|
22 | 7 | 23 | 0 | 30 |
| 0.027 | 1.607 | 5.753 | |
| 0.233 | 0.767 | 0.000 | 0.411 |
| 0.438 | 0.535 | 0.000 | |
| 0.096 | 0.315 | 0.000 | |
-------------------------|-----------|-----------|-----------|-----------|
na | 0 | 0 | 14 | 14 |
| 3.068 | 8.247 | 47.685 | |
| 0.000 | 0.000 | 1.000 | 0.192 |
| 0.000 | 0.000 | 1.000 | |
| 0.000 | 0.000 | 0.192 | |
-------------------------|-----------|-----------|-----------|-----------|
Column Total | 16 | 43 | 14 | 73 |
| 0.219 | 0.589 | 0.192 | |
-------------------------|-----------|-----------|-----------|-----------|
CrossTab: Age
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 73
| Genotype (5=FAD, 0=WT)
Age Harvested (6=young,14=old) | 0 | 5 | na | Row Total |
-------------------------------|-----------|-----------|-----------|-----------|
14 | 8 | 20 | 0 | 28 |
| 0.566 | 0.746 | 5.370 | |
| 0.286 | 0.714 | 0.000 | 0.384 |
| 0.500 | 0.465 | 0.000 | |
| 0.110 | 0.274 | 0.000 | |
-------------------------------|-----------|-----------|-----------|-----------|
6 | 8 | 23 | 0 | 31 |
| 0.214 | 1.230 | 5.945 | |
| 0.258 | 0.742 | 0.000 | 0.425 |
| 0.500 | 0.535 | 0.000 | |
| 0.110 | 0.315 | 0.000 | |
-------------------------------|-----------|-----------|-----------|-----------|
na | 0 | 0 | 14 | 14 |
| 3.068 | 8.247 | 47.685 | |
| 0.000 | 0.000 | 1.000 | 0.192 |
| 0.000 | 0.000 | 1.000 | |
| 0.000 | 0.000 | 0.192 | |
-------------------------------|-----------|-----------|-----------|-----------|
Column Total | 16 | 43 | 14 | 73 |
| 0.219 | 0.589 | 0.192 | |
-------------------------------|-----------|-----------|-----------|-----------|
Data Sparcity
No Filter
Filter
Log2 Transformation
Median Normalization
Peptide/Protein Group Inference
Protein groups are identified adopting the method used in MSDaPl [@Sharma2012] in which the parsimonious protein inference implemented is based on the IDPicker algorithm [@Ma2009]. The steps involved in the grouping of the indistinguishable protein groups are as follows:
- Step 1: A bipartitie graph is created with edges between peptides
and their matching proteins.
- Step 2: Peptides that match the same set of proteins are merged into
a single node in the graph. For example, peptides 3, 7, and 9 match
protein A and no other protein.
- Step 3: Proteins that match the same set of peptide are merged into
a single node in the graph. These proteins comprise an
indistinguishable protein group.
In this experiment, we report 6554 protein groups and
60562 non-redundant peptides inferred from
97756 peptides measured.
Batch Effect Adjustment
Peptide Group
Condition
No Adjustment
Batch Adjustment
Batch
No Adjustment
Batch Adjustment
Age
No Adjustment
Batch Adjustment
Genotype
No Adjustment
Batch Adjustment
Protein Group
Condition
No Adjustment
Batch Adjustment
Batch
No Adjustment
Batch Adjustment
Age
No Adjustment
Batch Adjustment
Genotype
No Adjustment
Batch Adjustment
Relative Standard Deviation
Peptide Group
MBRC2
CMR2
Protein Group
MBRC2
CMR2
Session Info
R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] tidyr_1.1.0 plotly_4.9.2.1 ggridges_0.5.2
[4] dplyr_1.0.0 ggplot2_3.3.2 scidata_0.0.0.9000
[7] readr_1.3.1 rmdformats_1.0.3.9000 knitr_1.29
[10] RevoUtils_11.0.2 RevoUtilsMath_11.0.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.5 RColorBrewer_1.1-2 plyr_1.8.6 pillar_1.4.6
[5] compiler_4.0.2 tools_4.0.2 digest_0.6.25 viridisLite_0.3.0
[9] jsonlite_1.6.1 evaluate_0.14 lifecycle_0.2.0 tibble_3.0.2
[13] gtable_0.3.0 pkgconfig_2.0.3 rlang_0.4.7 crosstalk_1.1.0.1
[17] yaml_2.2.1 xfun_0.21 httr_1.4.1 withr_2.2.0
[21] stringr_1.4.0 gtools_3.8.2 htmlwidgets_1.5.1 generics_0.0.2
[25] vctrs_0.3.1 hms_0.5.3 DT_0.14 grid_4.0.2
[29] tidyselect_1.1.0 glue_1.4.1 data.table_1.12.8 R6_2.3.0
[33] rmarkdown_2.10 bookdown_0.20 gdata_2.18.0 farver_2.0.3
[37] purrr_0.3.4 magrittr_1.5 MASS_7.3-51.6 gmodels_2.18.1
[41] scales_1.1.1 ellipsis_0.3.1 htmltools_0.5.1 colorspace_1.4-1
[45] labeling_0.3 stringi_1.4.6 lazyeval_0.2.2 munsell_0.5.0
[49] crayon_1.3.4